Knowledge incorporation and rule extraction in neural networks

Minoru Fukumi, Yasue Mitsukura, Norio Akamatsu

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper a new knowledge incorporation and rule extraction method in neural networks is presented. The rule form of an if–then type can be inserted into a neural network (NN) as knowledge of a problem. NN is then trained by using a set of training samples. In this case the structure learning algorithm with forgetting is used to generate a small-sized NN system. After the NN training, rules are extracted from it. The results of computer simulations show that this approach can generate obvious network architectures and as a result simple rules compared with conventional rule extraction methods.

本文言語English
ホスト出版物のタイトルArtificial Neural Networks - ICANN 2001 - International Conference, Proceedings
編集者Kurt Hornik, Georg Dorffner, Horst Bischof
出版社Springer Verlag
ページ1248-1253
ページ数6
ISBN(印刷版)3540424865, 9783540446682
DOI
出版ステータスPublished - 2001
外部発表はい
イベントInternational Conference on Artificial Neural Networks, ICANN 2001 - Vienna, Austria
継続期間: 2001 8月 212001 8月 25

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2130
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

OtherInternational Conference on Artificial Neural Networks, ICANN 2001
国/地域Austria
CityVienna
Period01/8/2101/8/25

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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